How to map geographically-detailed survey responses?

I am experimenting with the mapping/visualization of survey response data, with a particular focus on using transparency to convey uncertainty. See some examples here.

Do you think the examples are successful at communicating both local values of the variable of interest, as well as the lack of information in certain places? Also, do you have any general advice for choosing an approach to spatially smoothing the data in a way that preserves local features, but prevents individual respondents from standing out? I have experimented a lot with smoothing in these maps, and the cost of preventing the Midwest and West from looking “spotty” is the oversmoothing of the Northeast.

My quick impression is that the graphs are more pretty than they are informative. But “pretty” is not such a bad thing! The conveying-information part is more difficult: to me, the graphs seem to be displaying a somewhat confusing mix of opinion level and population density. Consider, for example, the bright red color in Dallas. There must be areas in the countryside that are also heavily Republican but Dallas stands out because there are a lot of people there. In some ways this makes sense—that’s where the voters are—but to me it makes the map a bit confusing. I’m also bothered by the blurriness of the entire northeast—I assume this is happening because all the cities are in each others’ penumbras. That’s just one problem though; really, what’s bugging me more is the overlay of intensity with density.

I think I’d prefer something simpler such as putting a colored circle in each county with the size of the circle proportional to population. But, as I said above, “pretty” is important too.

4 Comments

I think this is really hard to do in 2D, and I’ve never been keen on circles, given the difficulty of comparing areas by eye.

Surely someone is doing 3D graphical displays of such data.
People at SGI played with this back in the mid-1990s, although the best examples were ones we couldn’t talk about, because they were proprietary to Wall St firms who created interesting representations of the stock market to combine multiple attributes.

But, specifically we had a 3D US map application, where a vertical bar stood out from each state showing income.
Then there was a slider that controlled the year. Sliding back and forth, one could quickly notice state incomes that were changing quicker or in opposite directions from neighbors. For instance, the most striking events were temporary upward blips in Kansas and South Dakota …. which turned out to be synchronize with building missile bases.

We also had an app, originally designed as a hierarchical file system navigator (FSN) that let you start at the root of the tree, see the files in the distance as towers, and “fly” over and look at them. People actually saw a variant of that in Jurassic Park,
where the girl says UNIX system, I know this* and here’s an image.

For these geographic apps, if I were doing this, I’d try:
a) a 3D rotatable/zoomable map.
b) One variable as height, with a control to adjust the height scale.
c) Another variable as color, with a selection of palettes, perhaps.
d) A slider bar for years, if that’s relevant, or use a slide to provide cutoff values for the others.

Good 2D graphics are wonderful, as per Tufte, but at some point, it just gets too hard to do well.
In this case, I’d be tempted to have a bar per county or zip, with population, and use color for politics and see hwo that works, but one can never tell until you look at it.

*That line wasn’t in the book; the ILM guys had seen FSN and thought it was cool, so they got that little scene in.
I still have my T-shirt with a Jurassic Park logo, a dinosaur under construction, with scaffolding and silouettes of people at computers. It took special pleading with Spielberg to use the logo.

I actually like the focus of red bringing you to east Texas and around Atlanta. I think the density overlay is the only real problem. If the density of the answer was expressed only in the transparency of the red or blue over a white background, and not in a gray scale overlay, I’d think it an informative final version!